Including congestion effects in urban road traffic CO2 emissions modelling: Do Local Government Authorities have the right options?

Tailpipe emissions from vehicles on urban road networks have damaging impacts, with the problem exacerbated by the common occurrence of congestion. This article focuses on carbon dioxide because it is the largest constituent of road traffic greenhouse gas emissions. Local Government Authorities (LGAs) are typically responsible for facilitating mitigation of these emissions, and critical to this task is the ability to assess the impact of transport interventions on road traffic emissions for a whole network.This article presents a contemporary review of literature concerning road traffic data and its use by LGAs in emissions models (EMs). Emphasis on the practicalities of using data readily available to LGAs to estimate network level emissions and inform effective policy is a relatively new research area, and this article summarises achievements so far. Results of the literature review indicate that readily available data are aggregated at traffic level rather than disaggregated at individual vehicle level. Hence, a hypothesis is put forward that optimal EM complexity is one using traffic variables as inputs, allowing LGAs to capture the influence of congestion whilst avoiding the complexity of detailed EMs that estimate emissions at vehicle level.Existing methodologies for estimating network emissions based on traffic variables typically have limitations. Conclusions are that LGAs do not necessarily have the right options, and that more research in this domain is required, both to quantify accuracy and to further develop EMs that explicitly include congestion, whilst remaining within LGA resource constraints.     

Greenhouse gas emissions from road construction: An assessment of alternative staging approaches

The greenhouse gas (GHG) emissions associated with road construction activities are analyzed. The main focus of this analysis is on the vehicle emissions associated with alternative project staging approaches, specifically a full closure of the road during construction, versus an intermittent road closure. The analysis includes the direct and upstream emissions associated with materials, construction equipment, mobilization of resources to the work site, and maintenance activity associated with the project over its lifetime. The analysis is based on one case study of a road project in New Jersey. The assumptions underlying the staging analysis are based on hypothetical approaches. Results provide an assessment of the main sources of project related emissions and the ability to minimize total project emissions by minimizing traffic disruption. In the analysis with a full closure of the road, traffic disruption accounts for 26% of total emissions, while with an intermittent road closure, traffic disruption accounts for only 2% of total emissions. The other main sources are from materials and life-cycle maintenance. The analysis demonstrates the feasibility of minimizing project related GHG emissions during road construction activities.     

Strain prediction for critical positions of FPSO under different loading of stored oil using GAIFOA-BP neural network

FPSO (floating, production, storage and offloading) units are widely used in the offshore oil and gas industry. Generally, FPSOs have excellent oil storage capacity owing to their huge oil cargo holds. The volume and distribution of stored oil in the cargo holds influence the strain level of hull girder, especially at critical positions of FPSO. However, strain prediction using structural analysis tools is computationally expensive and time consuming. In this study, a prediction tool based on back-propagation (BP) neural network called GAIFOA-BP is proposed to predict the strain values of concerned positions of an FPSO model under different oil storage conditions. The GAIFOA-BP combines BP model and GAIFOA which is a combination of genetic algorithm (GA) and an improved fruit fly optimization algorithm (IFOA). Results from three benchmark tests show that the GAIFOA-BP model has a remarkable performance. Subsequently, a total of 81 sets of training data and 25 sets of testing data are obtained from experiment using fiber Bragg grating (FBG) sensors installed on the surface of an FPSO model. The numerical results show that the GAIFOA-BP is capable of predicting the strain values with higher accuracy as compared with other BP models. Finally, the reserved GAIFOA-BP model is utilized to predict the strain values under the inputs of a 10-day time series of volume and distribution of stored oil. The predicted strain results are further used to calculate the fatigue consumption of measurement points.     

基于多源数据的公交车能耗碳排放测算模型

公交车能耗碳排放强度与车辆、线路和驾驶员有显著相关关系，为精准刻画其能耗碳排放强度特征，整合OBD监测数据、加油(气)数据、运营排班数据等多源数据资源. OBD监测数据和加油(气)数据呈显著的线性关系，证明修正后的OBD监测数据可满足分析要求. 搭建“速度-能耗碳排放强度曲线”测算模型，幂函数关系的拟合优度R2 =0.972 6 为最高. 实证研究发现，平均速度在10~60 km/h 变化时，液化天然气(LNG)车比柴油车能耗碳排放强度高 3.3%~33.7%，双层车比铰接车高2.4%~13.3%；LNG铰接车在不同线路、相同速度下的强度相差9.6%；不同驾驶员在相同线路的能耗碳排放强度可相差24.2%. 模型为各城市基于多源数据开展公交能耗碳排放目标设定提供数据支撑.     

导电密封胶对不锈钢车体电阻点焊焊接性能影响研究

分析了电阻点焊原理,对相同的点焊搭接方式,分别采用3种工况进行焊接试验。3种工况分别采用相同焊接参数对搭接接触面涂导电密封胶和不涂导电密封胶的试件进行焊接;优化焊接参数后,对搭接接触面涂导电密封胶的试验件进行焊接。对3种工况下完成的焊接试件进行拉伸力检测试验、金相熔核尺寸检测和缺陷检测试验,对熔核直径、拉伸力、熔核内部缺陷的试验结果进行分析。试验结果表明:导电密封胶对电阻点焊的焊接性能存在影响;通过适当优化焊接参数,可以提高涂导电密封胶试件的焊接性能,焊接质量能够满足产品焊接要求。     

隧道瓦斯地段施工技术浅析

结合临吉高速公路S12合同段瓦窑岭隧道的瓦斯地段施工技术,从超前探孔、瓦斯监测、开挖支护及初衬等方面阐述了瓦斯隧道施工时的重点和注意事项。     

废气旁通阀开度对增压直喷汽油机部分负荷性能的影响

汽油机节气门产生的节流损失对增压发动机泵气损失的影响相当严重,尤其是在中小负荷时,针对这一问题采用试验的方法研究了中小负荷下旁通阀开度对增压直喷汽油机性能的影响。研究结果表明,在节气门开度较小的小负荷工况下,涡轮增压器不宜工作,否则排气背压过大,对发动机非常不利;而废气旁通阀全开可以减小排气背压,能使发动机的动力性和经济性提高3%左右。对废气旁通阀的合理控制可以实现发动机在自然吸气和涡轮增压两种模式之间的转换。     

羟基喜树碱对人胆管癌QBC939裸鼠移植瘤PS2、COX-2的影响

目的探讨羟基喜树碱对人胆管癌QBC939裸鼠移植瘤的乳癌相关肽(PS2)、环氧合酶-2(COX-2)的影响,分析PS2、COX-2与肿瘤发生、发展的关系。方法建立人胆管癌QBC939细胞株裸鼠皮下移植瘤模型,将30只裸鼠随机分成对照组、羟基喜树碱低剂量组和羟基喜树碱高剂量组,观察移植瘤体生长情况,RT-PCR法检测瘤体内PS2、COX-2 mRNA表达。结果与对照组比,羟基喜树碱低、高剂量组都可使移植瘤体的PS2 mRNA表达增高;COX-2 mRNA表达降低,且瘤体生长减慢,与对照组比较差异有统计学意义(P<0.01)。结论羟基喜树碱可降低移植瘤COX-2 mRNA表达,增高移植瘤体的PS2 mRNA表达,并使人胆管癌裸鼠移植瘤生长减慢。     

Study on T lymphocyte subsets and NK cells in patients with Graves＇ disease combined with type 2 diabetes

Objective To investigate changes in T lymphocyte subsets and NK cells in patients with simple Graves' disease (GD)and Graves' disease combined with type 2 diabetes mellitus (GD/T2DM). Methods Fifteen cases of GD/ T2DM were selected from our hospital from November 2001 to November 2004. Before and after therapy thyroid function, thyroglobulin antibody (TGA), thyroid microsomal antibody (TMA) and blood glucose level were measured, and T lymphocyte subsets (CD3, CD4, CD8, CD4/CD8) and NK cells (CD56) were measured by immunofluorescence double labeling monoclonal antibody and flow cytometry, respectively. At the same time, comparison was made with simple GD (15 cases), T2DM (15 cases) and healthy control (20 cases). Results Before therapy, CD4/CD8, CD4 and NK cells in GD/T2DM were less than normal, and there was no significant difference in comparison with simple GD (P<0.05). In T2DM group, only CD4/CD8 and CD4 were less than those of healthy controls (P<0.05). When thyroid function recovered after 1 to 3 months of methimazole treatment in both GD/T2DM and simple GD groups, various indexes recovered, which were more obvious in simple GD. Conclusion Immune hypofunction of GD may be the key to the immune abnormality of GD/T2DM, which is more significant than that of simple GD or T2DM. The recovery of thyroid function and immune abnormality is not consistent, and the recovery of GD is more significant than that of GD/T2DM.